People Watching: Human Actions as a Cue for Single-View Geometry

People

Abstract

We present an approach which exploits the coupling between
human actions and scene geometry. We investigate the use of human pose
as a cue for single-view 3D scene understanding. Our method builds upon
recent advances in still-image pose estimation to extract functional and
geometric constraints about the scene. These constraints are then used to
improve state-of-the-art single-view 3D scene understanding approaches.
The proposed method is validated on a collection of monocular time lapse sequences
collected from YouTube and a dataset of still images of
indoor scenes. We demonstrate that observing people performing different actions
can significantly improve estimates of 3D scene geometry.

Related Works

Funding

This research is supported by:

NSF Graduate Research Fellowship for David Fouhey

ONR-MURI Grant N000141010934

Qauero

OSEO

MSR-INRIA

EIT-ICT

ERC grant Videoworld

Copyright Notice

The documents contained in these directories are included by the
contributing authors as a means to ensure timely dissemination
of scholarly and technical work on a non-commercial basis.
Copyright and all rights therein are maintained by the authors
or by other copyright holders, notwithstanding that they have
offered their works here electronically. It is understood that
all persons copying this information will adhere to the terms
and constraints invoked by each author's copyright.